Sync ollama docs from 948f6933 on 2026-08-12
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title: VS Code
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---
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VS Code includes built-in AI chat through GitHub Copilot Chat. Ollama models can be used directly in the Copilot Chat model picker.
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Use Ollama models in VS Code Chat with the [Ollama extension](https://marketplace.visualstudio.com/items?itemName=Ollama.ollama).
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## Requirements
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- [Visual Studio Code 1.127 or newer](https://code.visualstudio.com/download)
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- Ollama installed and running
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- At least one local or cloud model available in Ollama
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Earlier VS Code versions do not reliably cancel requests from language model providers.
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## Prerequisites
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Ollama 0.17.6 or newer is recommended for cloud model sign-in and richer model metadata. Older versions may still work with local models.
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- Ollama v0.18.3+
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- [VS Code 1.113+](https://code.visualstudio.com/download)
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- [GitHub Copilot Chat extension 0.41.0+](https://marketplace.visualstudio.com/items?itemName=GitHub.copilot-chat)
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## Install the extension
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<Note> VS Code requires you to be logged in to use its model selector, even for custom models. This doesn't require a paid GitHub Copilot account; GitHub Copilot Free will enable model selection for custom models.</Note>
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1. Install the [Ollama extension](https://marketplace.visualstudio.com/items?itemName=Ollama.ollama) from the VS Code Marketplace.
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2. Open Chat in VS Code.
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3. Open the model picker at the bottom of the chat input.
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4. Choose a model from the **Ollama** section.
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## Quick setup
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The extension discovers models from `http://127.0.0.1:11434` by default.
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## Add a model
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Pull a local model:
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```shell
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ollama launch vscode
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ollama pull qwen3.6
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```
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Recommended models will be shown after running the command. See the latest models at [ollama.com](https://ollama.com/search?c=tools).
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Make sure **Local** is selected at the bottom of the Copilot Chat panel to use your Ollama models.
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<div style={{ display: "flex", justifyContent: "center" }}>
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<img
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src="/images/local.png"
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alt="Ollama Local Models"
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width="60%"
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style={{ borderRadius: "4px", marginTop: "10px", marginBottom: "10px" }}
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/>
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</div>
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## Run directly with a model
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To use a cloud model, pull it and sign in:
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```shell
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ollama launch vscode --model qwen3.5:cloud
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ollama pull kimi-k2.6:cloud
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ollama signin
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```
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Cloud models are also available at [ollama.com](https://ollama.com/search?c=cloud).
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## Manual setup
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Local models do not require sign-in.
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To configure Ollama manually without `ollama launch`:
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## Context length
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1. Open the **Copilot Chat** side bar from the top right corner
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<div style={{ display: "flex", justifyContent: "center" }}>
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<img
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src="/images/vscode-sidebar.png"
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alt="VS Code chat Sidebar"
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width="75%"
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style={{ borderRadius: "4px" }}
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/>
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</div>
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2. Click the **settings gear icon** (<Icon icon="gear" />) to bring up the Language Models window
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<div style={{ display: "flex", justifyContent: "center" }}>
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<img
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src="/images/vscode-other-models.png"
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alt="VS Code model picker"
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width="75%"
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style={{ borderRadius: "4px" }}
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/>
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</div>
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3. Click **Add Models** and select **Ollama** to load all your Ollama models into VS Code
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<div style={{ display: "flex", justifyContent: "center" }}>
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<img
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src="/images/vscode-add-ollama.png"
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alt="VS Code model options dropdown to add ollama models"
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width="75%"
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style={{ borderRadius: "4px" }}
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/>
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</div>
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VS Code may show a model's maximum supported context length even when Ollama allocates a smaller context at runtime.
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4. Click the **Unhide** button in the model picker to show your Ollama models
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<div style={{ display: "flex", justifyContent: "center" }}>
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<img
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src="/images/vscode-unhide.png"
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alt="VS Code unhide models button"
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width="75%"
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style={{ borderRadius: "4px" }}
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/>
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</div>
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For local models, open Ollama **Settings**, set the context length to at least 64k, reload the VS Code window, and resend your prompt. See [Context length](/context-length) for more information.
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## Troubleshooting
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If Ollama models do not appear in the model picker:
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1. Make sure Ollama is running.
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2. Run `ollama list` and confirm that models are available.
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3. Run **Ollama: Refresh Models** from the Command Palette.
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4. Run **Ollama: Diagnose Models** and check the **Ollama** output channel.
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If a cloud model asks you to sign in, run `ollama signin`.
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